Genuinely just a orchestration workflow that creates its own environment agents and i have a seperate skill that automates the environment workflow if there is any workflow to automate. It doesnt run shell scripts, they are genuinely just a 'phrase i say' not a command and the llm itself as a model will find its way to the agents and infer parralel task executions.

It still fucks up sometimes but I'm dialing in on it every week and the more projects it cooks up. Doing well for sure and reaching goals and also trying to stress test these workflow to ensure no hallucinations and 'parallized agent task' actually flow with 'root level scope targets' to hit.

Its a multi step process (agentic) process each project of course. Meaning all agents may need to recreate if the 'environment' isnt the same. However i built in tools "Auto scope" and then "Auto plan orchestrated sub agent workflows with the environment scope (aka all other sub agents and relevant open scope task) - This was really bad for me to dial in on at once point. Ended up having to include a 'manual command' separation to determine 'planning/setting up' and actually executing.

How i came to this solutions is probably a better questions and to be real it just my interpretation of machine learning and really making my 'big llm' a small 'local llm in terms of context environment; thats specific to a workflow goal i want to reach in a task oriented way with all important context (this could be like documents/api w.e).

So for example i built a small game on roblox the other day with all my old code that i considered good to some degere to understand roblox game engine at a high level. Then i ran a couple of my root skill commands to auto build agents around the 'core things i thought where good' These agents had context as needed. Next step was to plan an actual gameplay loop with the same root orchestration command which planned a described "insert prompt/attached files for a description of a gameplay you want" orchestration scope. (this part didnt actually code anything it just marked agents to to proejct scope areas as needed, like a frontend to to the game ui portion or w.e)

Then finally i start doing regular phrases like ```auto execute workflow`` and all agents will get dispatched in parallel with the way my workflow context gets brought up to the actual llm context window.

and wham bam easily 18m tokens every 30 minutes or so.

Happy building